Low-power and Lossy Networks (LLNs), e.g., sensor networks, have a myriad of applications, such as smart grid, smart cities, home and building automation, etc. Various challenges are presented with LLNs, such as lossy links, low bandwidth, battery operation, low memory and/or processing capability, etc. Large-scale IP smart object networks pose a number of technical challenges. For instance, the degree of density of such networks (such as Smart Grid networks with a large number of sensors and actuators, smart cities, or advanced metering infrastructure or “AMI” networks) may be extremely high: it is not rare for each node to see several hundreds of neighbors. Also, links are usually shared (e.g., using wireless mesh or powerline communication (PLC) is networks) and provide very limited capacity (from a few Kbits/s to a several dozens of KBits/s).
The computation of diverse paths is a well-known technical challenge in networks using distance vector routing protocols, such as many LLN routing protocols. The ability to build diverse paths is important for the Internet of Things (IoT) for a number of critical/real-time applications where “1+1” techniques consisting of duplicating critical packets and sending them along diverse paths is a strong requirement. Indeed, for such packets, links are so lossy that sending a single copy along a path has a high probability of being lost (and being retransmitted, which involves additional delays), especially when the path diameter increases, particularly since the path's Packet Error Rate (PER) increases exponentially with the path length. Note that the computation of diverse paths may also be used to load-balance traffic flows across diverse paths (not just for 1+1).
Current diverse path mechanisms rely on knowledge of the full network topology, for example, using a link-state database, computation devices configured with full topology information, etc. In the case of typical routing protocols (e.g., Distance Vector) in LLNs, however, the routing topology is generally not fully known, i.e., nodes have limited visibility within the network.